Pandas Profiling Report

Dataset statistics

Number of variables	28
Number of observations	17481
Missing cells	17942
Missing cells (%)	3.7%
Duplicate rows	0
Duplicate rows (%)	0.0%
Total size in memory	3.7 MiB
Average record size in memory	224.0 B

Variable types

NUM	16
CAT	10
UNSUPPORTED	1
BOOL	1

Reproduction

Analysis started	2020-08-11 00:44:57.143715
Analysis finished	2020-08-11 00:46:04.279553
Duration	1 minute and 7.14 seconds
Version	pandas-profiling v2.8.0
Command line	`pandas_profiling --config_file config.yaml [YOUR_FILE.csv]`
Download configuration	config.yaml

Warnings

`username` has a high cardinality: 10490 distinct values	High cardinality
`tweet` has a high cardinality: 16893 distinct values	High cardinality
`stopwords` has a high cardinality: 14801 distinct values	High cardinality
`clean_text` has a high cardinality: 16317 distinct values	High cardinality
`Start Date` has a high cardinality: 67 distinct values	High cardinality
`End Date` has a high cardinality: 67 distinct values	High cardinality
`Sample` has a high cardinality: 69 distinct values	High cardinality
`likes_count` is highly correlated with `retweets_count`	High correlation
`retweets_count` is highly correlated with `likes_count`	High correlation
`positive` is highly correlated with `Unnamed: 0` and 2 other fields	High correlation
`Unnamed: 0` is highly correlated with `positive`	High correlation
`date` is highly correlated with `positive` and 1 other fields	High correlation
`death` is highly correlated with `date` and 1 other fields	High correlation
`End Date` is highly correlated with `Poll` and 3 other fields	High correlation
`Poll` is highly correlated with `End Date` and 1 other fields	High correlation
`Start Date` is highly correlated with `End Date` and 2 other fields	High correlation
`Sample` is highly correlated with `Poll` and 3 other fields	High correlation
`MoE` is highly correlated with `Start Date` and 2 other fields	High correlation
`geo` has 17481 (100.0%) missing values	Missing
`death` has 453 (2.6%) missing values	Missing
`tweet` is uniformly distributed	Uniform
`clean_text` is uniformly distributed	Uniform
`Unnamed: 0` has unique values	Unique
`geo` is an unsupported type, check if it needs cleaning or further analysis	Unsupported
`replies_count` has 10882 (62.3%) zeros	Zeros
`retweets_count` has 11418 (65.3%) zeros	Zeros
`likes_count` has 8671 (49.6%) zeros	Zeros
`stopwords_count` has 683 (3.9%) zeros	Zeros
`Sentiment` has 4440 (25.4%) zeros	Zeros
`Topic` has 1130 (6.5%) zeros	Zeros

Unnamed: 0
Real number (ℝ_≥0)

HIGH CORRELATION
UNIQUE

Distinct count	17481
Unique (%)	100.0%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%

Mean	8740.0
Minimum	0
Maximum	17480
Zeros	1
Zeros (%)	< 0.1%
Memory size	136.6 KiB

Quantile statistics

Minimum	0
5-th percentile	874
Q1	4370
median	8740
Q3	13110
95-th percentile	16606
Maximum	17480
Range	17480
Interquartile range (IQR)	8740

Descriptive statistics

Standard deviation	5046.474363
Coefficient of variation (CV)	0.5773998127
Kurtosis	-1.2
Mean	8740
Median Absolute Deviation (MAD)	4370
Skewness	0
Sum	152783940
Variance	25466903.5

Histogram

Histogram with fixed size bins (bins=10)

Value	Count	Frequency (%)
2047	1	< 0.1%
4743	1	< 0.1%
8833	1	< 0.1%
14978	1	< 0.1%
12931	1	< 0.1%
2692	1	< 0.1%
645	1	< 0.1%
6790	1	< 0.1%
17037	1	< 0.1%
725	1	< 0.1%
Other values (17471)	17471	99.9%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	1	< 0.1%
1	1	< 0.1%
2	1	< 0.1%
3	1	< 0.1%
4	1	< 0.1%

Value	Count	Frequency (%)
17480	1	< 0.1%
17479	1	< 0.1%
17478	1	< 0.1%
17477	1	< 0.1%
17476	1	< 0.1%

date
Real number (ℝ_≥0)

HIGH CORRELATION

Distinct count	198
Unique (%)	1.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%

Mean	1.593644095417882e+18
Minimum	1579651200000000000
Maximum	1596672000000000000
Zeros	0
Zeros (%)	0.0%
Memory size	136.6 KiB

Quantile statistics

Minimum	1.5796512e+18
5-th percentile	1.5848352e+18
Q1	1.5937344e+18
median	1.5945984e+18
Q3	1.5955488e+18
95-th percentile	1.5964128e+18
Maximum	1.596672e+18
Range	1.70208e+16
Interquartile range (IQR)	1.8144e+15

Descriptive statistics

Standard deviation	3.422107929e+15
Coefficient of variation (CV)	0.002147347666
Kurtosis	4.790678816
Mean	1.593644095e+18
Median Absolute Deviation (MAD)	8.64e+14
Skewness	-2.291196015
Sum	3.908880699e+18
Variance	1.171082268e+31

Histogram

Histogram with fixed size bins (bins=10)

Value	Count	Frequency (%)
1.5945984e+18	591	3.4%
1.5939936e+18	549	3.1%
1.5941664e+18	514	2.9%
1.59408e+18	487	2.8%
1.594944e+18	484	2.8%
1.5948576e+18	455	2.6%
1.5943392e+18	450	2.6%
1.593648e+18	449	2.6%
1.5960672e+18	430	2.5%
1.5942528e+18	424	2.4%
Other values (188)	12648	72.4%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
1.5796512e+18	17	0.1%
1.5797376e+18	25	0.1%
1.579824e+18	16	0.1%
1.5799104e+18	16	0.1%
1.5799968e+18	18	0.1%

Value	Count	Frequency (%)
1.596672e+18	225	1.3%
1.5965856e+18	275	1.6%
1.5964992e+18	335	1.9%
1.5964128e+18	367	2.1%
1.5963264e+18	332	1.9%

username
Categorical

HIGH CARDINALITY

Distinct count	10490
Unique (%)	60.0%
Missing	0
Missing (%)	0.0%
Memory size	136.6 KiB

realdonaldtrump	2541
washingtonpost	576
nytimes	267
freddiesirmans	160
bornwildm	116
Other values (10485)	13821

Common Values
Length

Value	Count	Frequency (%)
realdonaldtrump	2541	14.5%
washingtonpost	576	3.3%
nytimes	267	1.5%
freddiesirmans	160	0.9%
bornwildm	116	0.7%
democratboricua	94	0.5%
nygovcuomo	83	0.5%
davidhamer_1951	59	0.3%
sudiptamalakar4	46	0.3%
ykhalim	45	0.3%
Other values (10480)	13494	77.2%

Length

Max length	15
Median length	12
Mean length	11.84285796
Min length	2

tweet
Categorical

HIGH CARDINALITY
UNIFORM

Distinct count	16893
Unique (%)	96.6%
Missing	0
Missing (%)	0.0%
Memory size	136.6 KiB

Time for #USA to default on all the bonds held by #China to pay for spreading #Covid_19 #COVID19 and causing trillions in damage to life and global economy. @realDonaldTrump @POTUS @SecPompeo #trump #usa #USCHINA #SouthChinaSea #Taiwan #HongKong #Vietnam #Huawei #BoycottChinese	25
#CHRIST is here since 1998 – to take back the earth. And Plagues, pestilence, and assaults, like Covid-19 will be used to destroy the USA and the 8th World Empire – and create God’s Kingdom on Earth. Daniel 2:32-45.	24
Something to think about: according to the WHO website on COVID-19 France and the UK have a death rate of over 18% if you have the virus! USA death rate is less than 4%!! That you won't hear from CDC, Fauci and the FAKE NEWS MEDIA!!!	21
COVID-19 and other measures FINISH THE USA & 8th World Empire off! I have told you & showed you – but you are too stupid to see what is right there before your eyes. The “Mirror” & events show you, narration tells you. Nature has a remedy for you. Daniel 2:32-45.	20
Banana republic COVID-19 cases in Canada are down 82% from their peak. COVID-19 cases in Italy are down 97% from their peak. COVID-19 cases in New Zealand are down 100% from their peak. COVID-19 cases in the USA are higher than ever and going up fast. #TrumpVirus	17
Other values (16888)	17374

Common Values
Length

Value	Count	Frequency (%)
Time for #USA to default on all the bonds held by #China to pay for spreading #Covid_19 #COVID19 and causing trillions in damage to life and global economy. @realDonaldTrump @POTUS @SecPompeo #trump #usa #USCHINA #SouthChinaSea #Taiwan #HongKong #Vietnam #Huawei #BoycottChinese	25	0.1%
#CHRIST is here since 1998 – to take back the earth. And Plagues, pestilence, and assaults, like Covid-19 will be used to destroy the USA and the 8th World Empire – and create God’s Kingdom on Earth. Daniel 2:32-45.	24	0.1%
Something to think about: according to the WHO website on COVID-19 France and the UK have a death rate of over 18% if you have the virus! USA death rate is less than 4%!! That you won't hear from CDC, Fauci and the FAKE NEWS MEDIA!!!	21	0.1%
COVID-19 and other measures FINISH THE USA & 8th World Empire off! I have told you & showed you – but you are too stupid to see what is right there before your eyes. The “Mirror” & events show you, narration tells you. Nature has a remedy for you. Daniel 2:32-45.	20	0.1%
Banana republic COVID-19 cases in Canada are down 82% from their peak. COVID-19 cases in Italy are down 97% from their peak. COVID-19 cases in New Zealand are down 100% from their peak. COVID-19 cases in the USA are higher than ever and going up fast. #TrumpVirus	17	0.1%
Well whatever anyone says about COVID-19, it is clearly NOT working in the USA, all thanks to your amazing president who prefers to deal with the deregulation of dishwashers! The USA's leaders behavior is beneath human dignity and inexcusable. How many more must die?	15	0.1%
45 maybe best friend is covid 19 and maybe russia are north korea are iran china take part in a way it help 45? 45 think it might could help him win again he knew it was on the way why was he so slow he call it a hoax well 45 cant fool usa people my own opinion.	13	0.1%
Huge DISCOUNT FIRST Time ever in Amazon History for Covid-19 and Independence day 2020 !!! Happy Learning !!! eBook on Amazon USA: https://amzn.to/2GOXJDD eBook on Amazon India: https://amzn.to/3b7yr1F	13	0.1%
Huge DISCOUNT FIRST Time ever in Amazon History for Covid-19 and Independence day 2020 !!! Happy Learning !!! eBook on Amazon USA: https://bit.ly/2RPuKWO eBook on Amazon India: https://bit.ly/2u7PY92	12	0.1%
LAW & ORDER!	12	0.1%
Other values (16883)	17309	99.0%

Length

Max length	1110
Median length	255
Mean length	233.9806647
Min length	10

replies_count
Real number (ℝ_≥0)

ZEROS

Distinct count	2681
Unique (%)	15.3%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%

Mean	2770.280018305589
Minimum	0
Maximum	193481
Zeros	10882
Zeros (%)	62.3%
Memory size	136.6 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	0
Q3	2
95-th percentile	18571
Maximum	193481
Range	193481
Interquartile range (IQR)	2

Descriptive statistics

Standard deviation	10481.30692
Coefficient of variation (CV)	3.783482844
Kurtosis	61.3258946
Mean	2770.280018
Median Absolute Deviation (MAD)	0
Skewness	6.51795077
Sum	48427265
Variance	109857794.8

Histogram

Histogram with fixed size bins (bins=10)

Value	Count	Frequency (%)
0	10882	62.3%
1	2209	12.6%
2	493	2.8%
3	174	1.0%
4	68	0.4%
5	58	0.3%
6	35	0.2%
7	32	0.2%
12	30	0.2%
13	30	0.2%
Other values (2671)	3470	19.9%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	10882	62.3%
1	2209	12.6%
2	493	2.8%
3	174	1.0%
4	68	0.4%

Value	Count	Frequency (%)
193481	1	< 0.1%
191133	1	< 0.1%
187705	1	< 0.1%
171777	1	< 0.1%
169276	1	< 0.1%

retweets_count
Real number (ℝ_≥0)

HIGH CORRELATION
ZEROS

Distinct count	2908
Unique (%)	16.6%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%

Mean	3567.0496539099595
Minimum	0
Maximum	216656
Zeros	11418
Zeros (%)	65.3%
Memory size	136.6 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	0
Q3	2
95-th percentile	26032
Maximum	216656
Range	216656
Interquartile range (IQR)	2

Descriptive statistics

Standard deviation	10643.6198
Coefficient of variation (CV)	2.98387206
Kurtosis	28.98592413
Mean	3567.049654
Median Absolute Deviation (MAD)	0
Skewness	4.367983486
Sum	62355595
Variance	113286642.4

Histogram

Histogram with fixed size bins (bins=10)

Value	Count	Frequency (%)
0	11418	65.3%
1	1343	7.7%
2	430	2.5%
3	214	1.2%
4	127	0.7%
5	75	0.4%
6	48	0.3%
7	44	0.3%
8	31	0.2%
10	31	0.2%
Other values (2898)	3720	21.3%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	11418	65.3%
1	1343	7.7%
2	430	2.5%
3	214	1.2%
4	127	0.7%

Value	Count	Frequency (%)
216656	1	< 0.1%
117144	1	< 0.1%
111753	1	< 0.1%
110900	1	< 0.1%
108547	1	< 0.1%

likes_count
Real number (ℝ_≥0)

HIGH CORRELATION
ZEROS

Distinct count	3169
Unique (%)	18.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%

Mean	16247.852640009152
Minimum	0
Maximum	808801
Zeros	8671
Zeros (%)	49.6%
Memory size	136.6 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	1
Q3	7
95-th percentile	115198
Maximum	808801
Range	808801
Interquartile range (IQR)	7

Descriptive statistics

Standard deviation	50416.4073
Coefficient of variation (CV)	3.102958182
Kurtosis	30.60619684
Mean	16247.85264
Median Absolute Deviation (MAD)	1
Skewness	4.693521632
Sum	284028712
Variance	2541814125

Histogram

Histogram with fixed size bins (bins=10)

Value	Count	Frequency (%)
0	8671	49.6%
1	2298	13.1%
2	943	5.4%
3	468	2.7%
4	300	1.7%
5	200	1.1%
6	148	0.8%
7	113	0.6%
8	83	0.5%
9	80	0.5%
Other values (3159)	4177	23.9%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	8671	49.6%
1	2298	13.1%
2	943	5.4%
3	468	2.7%
4	300	1.7%

Value	Count	Frequency (%)
808801	1	< 0.1%
707804	1	< 0.1%
620298	1	< 0.1%
581156	1	< 0.1%
561044	1	< 0.1%

video
Boolean

Distinct count	2
Unique (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	136.6 KiB

0	17102
1	379

Frequency Table

Value	Count	Frequency (%)
0	17102	97.8%
1	379	2.2%

geo
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing	17481
Missing (%)	100.0%
Memory size	136.7 KiB

positive
Real number (ℝ_≥0)

HIGH CORRELATION

Distinct count	187
Unique (%)	1.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%

Mean	3184083.3528402266
Minimum	2
Maximum	4852143
Zeros	0
Zeros (%)	0.0%
Memory size	136.6 KiB

Quantile statistics

Minimum	2
5-th percentile	42169
Q1	2786467
median	3350434
Q3	4093266
95-th percentile	4694126
Maximum	4852143
Range	4852141
Interquartile range (IQR)	1306799

Descriptive statistics

Standard deviation	1233987.308
Coefficient of variation (CV)	0.3875486824
Kurtosis	0.7947422338
Mean	3184083.353
Median Absolute Deviation (MAD)	618190
Skewness	-1.104340122
Sum	5.566096109e+10
Variance	1.522724676e+12

Histogram

Histogram with fixed size bins (bins=10)

Value	Count	Frequency (%)
3350434	591	3.4%
2928590	549	3.1%
3042503	514	2.9%
2980356	487	2.8%
3626881	484	2.8%
3549648	455	2.6%
3167984	450	2.6%
2732244	449	2.6%
4467852	430	2.5%
3101339	424	2.4%
Other values (177)	12648	72.4%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
2	120	0.7%
3	40	0.2%
4	8	< 0.1%
6	8	< 0.1%
7	11	0.1%

Value	Count	Frequency (%)
4852143	225	1.3%
4797959	275	1.6%
4745694	335	1.9%
4694126	367	2.1%
4644565	332	1.9%

death
Real number (ℝ_≥0)

HIGH CORRELATION
MISSING

Distinct count	162
Unique (%)	1.0%
Missing	453
Missing (%)	2.6%
Infinite	0
Infinite (%)	0.0%

Mean	121611.92858820765
Minimum	2.0
Maximum	151483.0
Zeros	0
Zeros (%)	0.0%
Memory size	136.6 KiB

Quantile statistics

Minimum	2
5-th percentile	27862
Q1	122446
median	127909
Q3	137602
95-th percentile	147631
Maximum	151483
Range	151481
Interquartile range (IQR)	15156

Descriptive statistics

Standard deviation	32335.62998
Coefficient of variation (CV)	0.2658919265
Kurtosis	6.577441345
Mean	121611.9286
Median Absolute Deviation (MAD)	6714.5
Skewness	-2.637883169
Sum	2070807920
Variance	1045592966

Histogram

Histogram with fixed size bins (bins=10)

Value	Count	Frequency (%)
127909	591	3.4%
122898	549	3.1%
124628	514	2.9%
123821	487	2.8%
131401	484	2.8%
130450	455	2.6%
126349	450	2.6%
121542	449	2.6%
144114	430	2.5%
125495	424	2.4%
Other values (152)	12195	69.8%
(Missing)	453	2.6%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
2	26	0.1%
4	17	0.1%
5	9	0.1%
8	20	0.1%
11	28	0.2%

Value	Count	Frequency (%)
151483	225	1.3%
150232	275	1.6%
148807	335	1.9%
147631	367	2.1%
147112	332	1.9%

word_count
Real number (ℝ_≥0)

Distinct count	74
Unique (%)	0.4%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%

Mean	35.87180367255878
Minimum	1
Maximum	91
Zeros	0
Zeros (%)	0.0%
Memory size	136.6 KiB

Quantile statistics

Minimum	1
5-th percentile	12
Q1	27
median	38
Q3	46
95-th percentile	52
Maximum	91
Range	90
Interquartile range (IQR)	19

Descriptive statistics

Standard deviation	12.66401258
Coefficient of variation (CV)	0.3530352891
Kurtosis	-0.3207170802
Mean	35.87180367
Median Absolute Deviation (MAD)	9
Skewness	-0.5744950938
Sum	627075
Variance	160.3772146

Histogram

Histogram with fixed size bins (bins=10)

Value	Count	Frequency (%)
47	701	4.0%
45	671	3.8%
46	658	3.8%
43	655	3.7%
42	644	3.7%
44	594	3.4%
48	590	3.4%
41	553	3.2%
38	540	3.1%
39	539	3.1%
Other values (64)	11336	64.8%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
1	4	< 0.1%
2	39	0.2%
3	78	0.4%
4	110	0.6%
5	87	0.5%

Value	Count	Frequency (%)
91	1	< 0.1%
90	1	< 0.1%
86	1	< 0.1%
83	1	< 0.1%
81	1	< 0.1%

avg_word_length
Real number (ℝ_≥0)

Distinct count	3807
Unique (%)	21.8%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%

Mean	5.865800014049402
Minimum	3.0526315789473686
Maximum	122.11111111111113
Zeros	0
Zeros (%)	0.0%
Memory size	136.6 KiB

Quantile statistics

Minimum	3.052631579
5-th percentile	4.086956522
Q1	4.636363636
median	5.244444444
Q3	6.368421053
95-th percentile	9.6
Maximum	122.1111111
Range	119.0584795
Interquartile range (IQR)	1.732057416

Descriptive statistics

Standard deviation	2.266082755
Coefficient of variation (CV)	0.3863211752
Kurtosis	409.0140737
Mean	5.865800014
Median Absolute Deviation (MAD)	0.7444444444
Skewness	10.32991592
Sum	102540.05
Variance	5.135131051

Histogram

Histogram with fixed size bins (bins=10)

Value	Count	Frequency (%)
5	170	1.0%
6	132	0.8%
4.5	101	0.6%
4.6	88	0.5%
4	83	0.5%
5.5	81	0.5%
7	73	0.4%
4.666666667	69	0.4%
4.833333333	69	0.4%
4.75	67	0.4%
Other values (3797)	16548	94.7%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
3.052631579	1	< 0.1%
3.146341463	1	< 0.1%
3.153846154	1	< 0.1%
3.2	1	< 0.1%
3.213114754	1	< 0.1%

Value	Count	Frequency (%)
122.1111111	1	< 0.1%
36	1	< 0.1%
31.75	2	< 0.1%
27.42857143	1	< 0.1%
24.66666667	1	< 0.1%

stopwords_count
Real number (ℝ_≥0)

ZEROS

Distinct count	36
Unique (%)	0.2%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%

Mean	12.270064641610892
Minimum	0
Maximum	36
Zeros	683
Zeros (%)	3.9%
Memory size	136.6 KiB

Quantile statistics

Minimum	0
5-th percentile	1
Q1	7
median	13
Q3	17
95-th percentile	23
Maximum	36
Range	36
Interquartile range (IQR)	10

Descriptive statistics

Standard deviation	6.595357673
Coefficient of variation (CV)	0.537516131
Kurtosis	-0.6328511159
Mean	12.27006464
Median Absolute Deviation (MAD)	5
Skewness	0.03848289588
Sum	214493
Variance	43.49874284

Histogram

Histogram with fixed size bins (bins=10)

Value	Count	Frequency (%)
15	1002	5.7%
13	987	5.6%
14	958	5.5%
12	942	5.4%
17	932	5.3%
16	910	5.2%
10	863	4.9%
11	838	4.8%
18	806	4.6%
7	777	4.4%
Other values (26)	8466	48.4%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	683	3.9%
1	307	1.8%
2	432	2.5%
3	519	3.0%
4	611	3.5%

Value	Count	Frequency (%)
36	1	< 0.1%
35	2	< 0.1%
33	4	< 0.1%
32	7	< 0.1%
31	10	0.1%

char_count
Real number (ℝ_≥0)

Distinct count	457
Unique (%)	2.6%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%

Mean	233.98066472169785
Minimum	10
Maximum	1110
Zeros	0
Zeros (%)	0.0%
Memory size	136.6 KiB

Quantile statistics

Minimum	10
5-th percentile	93
Q1	186
median	255
Q3	279
95-th percentile	339
Maximum	1110
Range	1100
Interquartile range (IQR)	93

Descriptive statistics

Standard deviation	75.58009128
Coefficient of variation (CV)	0.3230185339
Kurtosis	1.168054904
Mean	233.9806647
Median Absolute Deviation (MAD)	40
Skewness	-0.3282054299
Sum	4090216
Variance	5712.350198

Histogram

Histogram with fixed size bins (bins=10)

Value	Count	Frequency (%)
280	756	4.3%
279	667	3.8%
278	476	2.7%
277	361	2.1%
276	311	1.8%
275	255	1.5%
274	235	1.3%
273	188	1.1%
271	184	1.1%
272	182	1.0%
Other values (447)	13866	79.3%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
10	5	< 0.1%
11	1	< 0.1%
12	12	0.1%
13	3	< 0.1%
16	3	< 0.1%

Value	Count	Frequency (%)
1110	1	< 0.1%
602	1	< 0.1%
601	1	< 0.1%
595	1	< 0.1%
594	1	< 0.1%

stopwords
Categorical

HIGH CARDINALITY

Distinct count	14801
Unique (%)	84.7%
Missing	0
Missing (%)	0.0%
Memory size	136.6 KiB

[]	683
['and']	112
['of', 'of', 'and', 'of', 'and', 'in', 'below']	51
['in', 'for', 'and', 'on', 'on']	47
['you']	43
Other values (14796)	16545

Common Values
Length

Value	Count	Frequency (%)
[]	683	3.9%
['and']	112	0.6%
['of', 'of', 'and', 'of', 'and', 'in', 'below']	51	0.3%
['in', 'for', 'and', 'on', 'on']	47	0.3%
['you']	43	0.2%
['for', 'to', 'on', 'all', 'the', 'by', 'to', 'for', 'and', 'in', 'to', 'and']	34	0.2%
['to', 'and', 'for']	34	0.2%
['into', 'than', 'and', 'is', 'more', 'the', 'of', 'the']	32	0.2%
['of', 'at', 'is', 'than', 'and', 'is', 'at']	31	0.2%
['just', 'our', 'do', 'you', 'is', 'it', 'the', 'just', 'that', 'you', 'the', 'to', 'through', 'this', 'but', 'then']	28	0.2%
Other values (14791)	16386	93.7%

Length

Max length	242
Median length	86
Mean length	84.70791145
Min length	2

clean_text
Categorical

HIGH CARDINALITY
UNIFORM

Distinct count	16317
Unique (%)	93.4%
Missing	8
Missing (%)	< 0.1%
Memory size	136.6 KiB

huge discount first time ever amazon history covid independence happy learning ebook amazon ebook amazon india	47
julycoronavirus covid status total increase confirmed cases death test hospitalisation worldwide state newyorkcity please detail supporting reports facebook link	39
time default bonds held china spreading covid_ covid causing trillions damage life global economy realdonaldtrump potus secpompeo trump uschina southchinasea taiwan hongkong vietnam huawei boycottchinese	32
heads lets minds together think nothing democrats whyre good like know help covid nasty president sorry want yall safe	28
corner covid experience deaths million population lower belgium spain italy sweden france netherlands ireland	28
Other values (16312)	17299

Common Values
Length

Value	Count	Frequency (%)
huge discount first time ever amazon history covid independence happy learning ebook amazon ebook amazon india	47	0.3%
julycoronavirus covid status total increase confirmed cases death test hospitalisation worldwide state newyorkcity please detail supporting reports facebook link	39	0.2%
time default bonds held china spreading covid_ covid causing trillions damage life global economy realdonaldtrump potus secpompeo trump uschina southchinasea taiwan hongkong vietnam huawei boycottchinese	32	0.2%
heads lets minds together think nothing democrats whyre good like know help covid nasty president sorry want yall safe	28	0.2%
corner covid experience deaths million population lower belgium spain italy sweden france netherlands ireland	28	0.2%
christ since take back earth plagues pestilence assaults like covid used destroy world empire create gods kingdom earth daniel	24	0.1%
something think according website covid france death rate virus death rate less wont hear fauci fake news media	21	0.1%
covid measures finish world empire told showed stupid right eyes mirror events show narration tells nature remedy daniel	20	0.1%
terms covid cases canadas experience million lower sweden spain iceland belgium ireland portugal italy switzerland netherlands	19	0.1%
thank	19	0.1%
Other values (16307)	17196	98.4%

Length

Max length	251
Median length	137
Mean length	129.2029632
Min length	3

Sentiment
Real number (ℝ)

ZEROS

Distinct count	2402
Unique (%)	13.7%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%

Mean	0.05259328353233437
Minimum	-1.0
Maximum	1.0
Zeros	4440
Zeros (%)	25.4%
Memory size	136.6 KiB

Quantile statistics

Minimum	-1
5-th percentile	-0.4
Q1	-0.05436507937
median	0
Q3	0.2
95-th percentile	0.5
Maximum	1
Range	2
Interquartile range (IQR)	0.2543650794

Descriptive statistics

Standard deviation	0.2759058896
Coefficient of variation (CV)	5.246028981
Kurtosis	1.813930034
Mean	0.05259328353
Median Absolute Deviation (MAD)	0.1333333333
Skewness	0.05193317762
Sum	919.3831894
Variance	0.07612405991

Histogram

Histogram with fixed size bins (bins=10)

Value	Count	Frequency (%)
0	4440	25.4%
0.5	422	2.4%
0.2	418	2.4%
0.25	381	2.2%
-0.2	307	1.8%
0.1	296	1.7%
-0.1	279	1.6%
0.4	257	1.5%
-0.5	241	1.4%
0.8	223	1.3%
Other values (2392)	10217	58.4%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
-1	76	0.4%
-0.9	6	< 0.1%
-0.9	1	< 0.1%
-0.875	2	< 0.1%
-0.8666666667	1	< 0.1%

Value	Count	Frequency (%)
1	71	0.4%
0.9333333333	1	< 0.1%
0.925	1	< 0.1%
0.9	20	0.1%
0.875	1	< 0.1%

Poll
Categorical

HIGH CORRELATION

Distinct count	20
Unique (%)	0.1%
Missing	0
Missing (%)	0.0%
Memory size	136.6 KiB

Economist/YouGovYouGov	5196
The Hill/HarrisXThe Hill	2944
RCP Average	1553
EmersonEmerson	1245
QuinnipiacQuinnipiac	1180
Other values (15)	5363

Common Values
Length

Value	Count	Frequency (%)
Economist/YouGovYouGov	5196	29.7%
The Hill/HarrisXThe Hill	2944	16.8%
RCP Average	1553	8.9%
EmersonEmerson	1245	7.1%
QuinnipiacQuinnipiac	1180	6.8%
CBS News/YouGovCBS News	1143	6.5%
FOX NewsFOX News	1010	5.8%
Rasmussen ReportsRasmussen	957	5.5%
NBC News/Wall St. JrnlNBC/WSJ	582	3.3%
IBD/TIPPIBD/TIPP	502	2.9%
Other values (10)	1169	6.7%

Length

Max length	29
Median length	22
Mean length	20.37606544
Min length	6

Start Date
Categorical

HIGH CARDINALITY
HIGH CORRELATION

Distinct count	67
Unique (%)	0.4%
Missing	0
Missing (%)	0.0%
Memory size	136.6 KiB

2020-07-09	2603
2020-07-05	1875
2020-07-29	1780
2020-06-28	1664
2020-07-21	1392
Other values (62)	8167

Common Values
Length

Value	Count	Frequency (%)
2020-07-09	2603	14.9%
2020-07-05	1875	10.7%
2020-07-29	1780	10.2%
2020-06-28	1664	9.5%
2020-07-21	1392	8.0%
2020-07-03	1256	7.2%
2020-07-12	837	4.8%
2020-08-02	835	4.8%
2020-07-17	759	4.3%
2020-07-19	723	4.1%
Other values (57)	3757	21.5%

Length

Max length	10
Median length	10
Mean length	10
Min length	10

End Date
Categorical

HIGH CARDINALITY
HIGH CORRELATION

Distinct count	67
Unique (%)	0.4%
Missing	0
Missing (%)	0.0%
Memory size	136.6 KiB

2020-07-21	1933
2020-07-07	1875
2020-06-30	1675
2020-07-04	1256
2020-08-05	1178
Other values (62)	9564

Common Values
Length

Value	Count	Frequency (%)
2020-07-21	1933	11.1%
2020-07-07	1875	10.7%
2020-06-30	1675	9.6%
2020-07-04	1256	7.2%
2020-08-05	1178	6.7%
2020-07-30	1081	6.2%
2020-07-24	1049	6.0%
2020-07-13	1013	5.8%
2020-07-28	854	4.9%
2020-07-15	837	4.8%
Other values (57)	4730	27.1%

Length

Max length	10
Median length	10
Mean length	10
Min length	10

Sample
Categorical

HIGH CARDINALITY
HIGH CORRELATION

Distinct count	69
Unique (%)	0.4%
Missing	0
Missing (%)	0.0%
Memory size	136.6 KiB

1165 RV	1875
1198 RV	1664
--	1553
933 RV	1256
964 LV	1081
Other values (64)	10052

Common Values
Length

Value	Count	Frequency (%)
1165 RV	1875	10.7%
1198 RV	1664	9.5%
--	1553	8.9%
933 RV	1256	7.2%
964 LV	1081	6.2%
1401 LV	1049	6.0%
1273 RV	1013	5.8%
2500 LV	957	5.5%
1104 RV	837	4.8%
2850 RV	835	4.8%
Other values (59)	5361	30.7%

Length

Max length	8
Median length	7
Mean length	6.319489732
Min length	2

MoE
Categorical

HIGH CORRELATION

Distinct count	20
Unique (%)	0.1%
Missing	0
Missing (%)	0.0%
Memory size	136.6 KiB

--	2910
3.4	2232
3.2	2161
3.6	2100
1.8	1594
Other values (15)	6484

Common Values
Length

Value	Count	Frequency (%)
--	2910	16.6%
3.4	2232	12.8%
3.2	2161	12.4%
3.6	2100	12.0%
1.8	1594	9.1%
3.1	1506	8.6%
2.8	1157	6.6%
3	1094	6.3%
2	1017	5.8%
3.3	760	4.3%
Other values (10)	950	5.4%

Length

Max length	3
Median length	3
Mean length	2.575996797
Min length	1

Biden (D)
Real number (ℝ_≥0)

Distinct count	15
Unique (%)	0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%

Mean	48.567719238029866
Minimum	42.0
Maximum	56.0
Zeros	0
Zeros (%)	0.0%
Memory size	136.6 KiB

Quantile statistics

Minimum	42
5-th percentile	43
Q1	48
median	49
Q3	50
95-th percentile	52
Maximum	56
Range	14
Interquartile range (IQR)	2

Descriptive statistics

Standard deviation	2.762877214
Coefficient of variation (CV)	0.05688711057
Kurtosis	0.3932028498
Mean	48.56771924
Median Absolute Deviation (MAD)	1
Skewness	-0.5818357514
Sum	849012.3
Variance	7.633490501

Histogram

Histogram with fixed size bins (bins=10)

Value	Count	Frequency (%)
49	4987	28.5%
48	2583	14.8%
43	2136	12.2%
50	1599	9.1%
51	1545	8.8%
49.6	1210	6.9%
52	1207	6.9%
45	839	4.8%
55	348	2.0%
49.1	343	2.0%
Other values (5)	684	3.9%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
42	77	0.4%
43	2136	12.2%
45	839	4.8%
46	73	0.4%
47	258	1.5%

Value	Count	Frequency (%)
56	70	0.4%
55	348	2.0%
53	206	1.2%
52	1207	6.9%
51	1545	8.8%

Trump (R)
Real number (ℝ_≥0)

Distinct count	17
Unique (%)	0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%

Mean	41.07357130598936
Minimum	36.0
Maximum	52.0
Zeros	0
Zeros (%)	0.0%
Memory size	136.6 KiB

Quantile statistics

Minimum	36
5-th percentile	37
Q1	40
median	40.9
Q3	41
95-th percentile	46
Maximum	52
Range	16
Interquartile range (IQR)	1

Descriptive statistics

Standard deviation	2.474917075
Coefficient of variation (CV)	0.06025570692
Kurtosis	1.671302517
Mean	41.07357131
Median Absolute Deviation (MAD)	0.9
Skewness	1.088993899
Sum	718007.1
Variance	6.125214528

Histogram

Histogram with fixed size bins (bins=10)

Value	Count	Frequency (%)
40	5326	30.5%
41	3508	20.1%
39	1273	7.3%
40.9	1210	6.9%
46	1205	6.9%
45	1028	5.9%
37	1013	5.8%
38	776	4.4%
42	647	3.7%
43	578	3.3%
Other values (7)	917	5.2%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
36	10	0.1%
37	1013	5.8%
38	776	4.4%
39	1273	7.3%
40	5326	30.5%

Value	Count	Frequency (%)
52	71	0.4%
50	75	0.4%
48	14	0.1%
47	140	0.8%
46	1205	6.9%

Spread
Real number (ℝ)

Distinct count	18
Unique (%)	0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%

Mean	7.494147932040501
Minimum	-4.0
Maximum	15.0
Zeros	103
Zeros (%)	0.6%
Memory size	136.6 KiB

Quantile statistics

Minimum	-4
5-th percentile	3
Q1	4
median	8
Q3	9
95-th percentile	15
Maximum	15
Range	19
Interquartile range (IQR)	5

Descriptive statistics

Standard deviation	3.22160924
Coefficient of variation (CV)	0.4298833262
Kurtosis	0.4642815613
Mean	7.494147932
Median Absolute Deviation (MAD)	2
Skewness	0.129853082
Sum	131005.2
Variance	10.37876609

Histogram

Histogram with fixed size bins (bins=10)

Value	Count	Frequency (%)
9	3987	22.8%
4	2605	14.9%
7	1962	11.2%
3	1720	9.8%
10	1497	8.6%
8.7	1210	6.9%
8	1186	6.8%
15	1013	5.8%
6	864	4.9%
11	434	2.5%
Other values (8)	1003	5.7%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
-4	71	0.4%
0	103	0.6%
1	73	0.4%
2	84	0.5%
3	1720	9.8%

Value	Count	Frequency (%)
15	1013	5.8%
14	142	0.8%
12	85	0.5%
11	434	2.5%
10	1497	8.6%

Topic
Real number (ℝ_≥0)

ZEROS

Distinct count	10
Unique (%)	0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%

Mean	4.913391682398032
Minimum	0
Maximum	9
Zeros	1130
Zeros (%)	6.5%
Memory size	136.6 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	3
median	5
Q3	7
95-th percentile	9
Maximum	9
Range	9
Interquartile range (IQR)	4

Descriptive statistics

Standard deviation	2.684186199
Coefficient of variation (CV)	0.5463000657
Kurtosis	-1.082965326
Mean	4.913391682
Median Absolute Deviation (MAD)	2
Skewness	-0.1696933451
Sum	85891
Variance	7.20485555

Histogram

Histogram with fixed size bins (bins=10)

Value	Count	Frequency (%)
3	3515	20.1%
8	2916	16.7%
5	2321	13.3%
6	2138	12.2%
9	1397	8.0%
7	1346	7.7%
1	1266	7.2%
0	1130	6.5%
2	742	4.2%
4	710	4.1%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	1130	6.5%
1	1266	7.2%
2	742	4.2%
3	3515	20.1%
4	710	4.1%

Value	Count	Frequency (%)
9	1397	8.0%
8	2916	16.7%
7	1346	7.7%
6	2138	12.2%
5	2321	13.3%

Target
Categorical

Distinct count	2
Unique (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	136.6 KiB

Bad Response	11858
Good Response	5623

Common Values
Length

Value	Count	Frequency (%)
Bad Response	11858	67.8%
Good Response	5623	32.2%

Length

Max length	13
Median length	12
Mean length	12.32166352
Min length	12

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

Cramér's V (φc)

Cramér's V is an association measure for nominal random variables. The coefficient ranges from 0 to 1, with 0 indicating independence and 1 indicating perfect association. The empirical estimators used for Cramér's V have been proved to be biased, even for large samples. We use a bias-corrected measure that has been proposed by Bergsma in 2013 that can be found here.

First rows

	Unnamed: 0	date	username	tweet	replies_count	retweets_count	likes_count	geo	positive	death	word_count	avg_word_length	stopwords_count	char_count	stopwords	clean_text	Sentiment	Poll	Start Date	End Date	Sample	MoE	Biden (D)	Trump (R)	Spread	Topic	Target
0	0	1579651200000000000	realdonaldtrump	Making great progress in @Davos. Tremendous numbers of companies will be coming, or returning, to the USA. Hottest Economy! JOBS, JOBS, JOBS!	9465	17624	88225	NaN	2	NaN	22	5.454545	7	141	['in', 'of', 'will', 'be', 'or', 'to', 'the']	making great progress davos tremendous numbers companies coming returning hottest economy jobs jobs jobs	0.566667	ABC News/Wash PostABC/WP	2020-01-20	2020-01-23	880 RV	4	50.0	46.0	4.0	0	Bad Response
1	1	1579651200000000000	realdonaldtrump	Sorry, if you come you will be immediately sent back! https://twitter.com/DHSgov/status/1220103171403665410 …	8643	24619	98960	NaN	2	NaN	11	8.166667	5	109	['if', 'you', 'you', 'will', 'be']	sorry come immediately sent back	-0.250000	ABC News/Wash PostABC/WP	2020-01-20	2020-01-23	880 RV	4	50.0	46.0	4.0	3	Bad Response
2	2	1579651200000000000	realdonaldtrump	See you on Friday...Big Crowd! https://twitter.com/March_for_Life/status/1091025377932263427 …	7035	24342	97513	NaN	2	NaN	6	12.571429	2	94	['you', 'on']	fridaybig crowd	0.000000	ABC News/Wash PostABC/WP	2020-01-20	2020-01-23	880 RV	4	50.0	46.0	4.0	0	Bad Response
3	3	1579651200000000000	realdonaldtrump	True! https://twitter.com/RandPaul/status/1220044346373877761 …	3436	12031	50605	NaN	2	NaN	2	20.333333	0	63	[]	true	0.350000	ABC News/Wash PostABC/WP	2020-01-20	2020-01-23	880 RV	4	50.0	46.0	4.0	9	Good Response
4	4	1579651200000000000	realdonaldtrump	“NO PRESSURE”	18086	19899	122408	NaN	2	NaN	2	6.000000	0	13	[]	pressure	0.000000	ABC News/Wash PostABC/WP	2020-01-20	2020-01-23	880 RV	4	50.0	46.0	4.0	5	Bad Response
5	5	1579651200000000000	realdonaldtrump	Will be Great! https://twitter.com/WhiteHouse/status/1219708789957578752 …	2228	8103	39527	NaN	2	NaN	4	14.000000	1	74	['be']	great	0.800000	ABC News/Wash PostABC/WP	2020-01-20	2020-01-23	880 RV	4	50.0	46.0	4.0	3	Bad Response
6	6	1579651200000000000	realdonaldtrump	Great working with you Maria! https://twitter.com/MariaBartiromo/status/1219736663930417155 …	1777	7588	36498	NaN	2	NaN	6	12.428571	2	93	['with', 'you']	great working maria	0.800000	ABC News/Wash PostABC/WP	2020-01-20	2020-01-23	880 RV	4	50.0	46.0	4.0	1	Bad Response
7	7	1579651200000000000	realdonaldtrump	One of the many great things about our just signed giant Trade Deal with China is that it will bring both the USA & China closer together in so many other ways. Terrific working with President Xi, a man who truly loves his country. Much more to come!	8460	19473	102575	NaN	2	NaN	48	4.229167	21	250	['of', 'the', 'about', 'our', 'just', 'with', 'is', 'that', 'it', 'will', 'both', 'the', 'in', 'so', 'other', 'with', 'a', 'who', 'his', 'more', 'to']	many great things signed giant trade deal china bring china closer together many ways terrific working president truly loves country much come	0.333333	ABC News/Wash PostABC/WP	2020-01-20	2020-01-23	880 RV	4	50.0	46.0	4.0	5	Bad Response
8	8	1579651200000000000	realdonaldtrump	Will be interviewed at 5:00 A.M. Eastern by @JoeSquawk on @CNBC at the World Economic Forum in Davos, Switzerland. Enjoy!	2116	4824	23572	NaN	2	NaN	20	5.100000	7	121	['be', 'at', 'by', 'on', 'at', 'the', 'in']	interviewed eastern joesquawk cnbc world economic forum davos switzerland enjoy	0.300000	ABC News/Wash PostABC/WP	2020-01-20	2020-01-23	880 RV	4	50.0	46.0	4.0	5	Bad Response
9	9	1579651200000000000	realdonaldtrump	“Not the Senate’s job to mop up the mess made in the House by the Democrats. Biden admitted that he went to Ukraine and did the Quid Pro Quo.” @SteveScalise @FoxNews	10559	21869	89693	NaN	2	NaN	31	4.354839	14	165	['the', 'to', 'up', 'the', 'in', 'the', 'by', 'the', 'that', 'he', 'to', 'and', 'did', 'the']	senates mess made house democrats biden admitted went ukraine quid stevescalise foxnews	-0.175000	ABC News/Wash PostABC/WP	2020-01-20	2020-01-23	880 RV	4	50.0	46.0	4.0	5	Bad Response

Last rows

	Unnamed: 0	date	username	tweet	replies_count	retweets_count	likes_count	geo	positive	death	word_count	avg_word_length	stopwords_count	char_count	stopwords	clean_text	Sentiment	Poll	Start Date	End Date	Sample	MoE	Biden (D)	Trump (R)	Spread	Topic	Target
17471	17471	1596672000000000000	mat945	In times of challenge people become vulnerable and seek strong, proactive, cohesive, bipartisan government to lead them back - recent events in the USA suggest federal and state governments are either unwilling or unable to stand together as one in the fight against COVID-19.	0	0	0	NaN	4852143	151483.0	44	5.295455	14	276	['of', 'and', 'to', 'them', 'in', 'the', 'and', 'are', 'or', 'to', 'as', 'in', 'the', 'against']	times challenge people become vulnerable seek strong proactive cohesive bipartisan government lead back recent events suggest federal state governments either unwilling unable stand together fight covid	-0.113333	The Hill/HarrisXThe Hill	2020-08-02	2020-08-05	2850 RV	1.8	43.0	40.0	3.0	6	Good Response
17472	17472	1596672000000000000	allangpaterson	The USA will top 5million Covid-19 cases today, what a dark and demeaning statistic for the President.\n https://www.worldometers.info/coronavirus/	0	0	1	NaN	4852143	151483.0	18	7.111111	6	147	['will', 'what', 'a', 'and', 'for', 'the']	million covid cases today dark demeaning statistic president	-0.150000	The Hill/HarrisXThe Hill	2020-08-02	2020-08-05	2850 RV	1.8	43.0	40.0	3.0	6	Good Response
17473	17473	1596672000000000000	carolynguzzi	Like opposite Day in high school! This is all a political ploy and after the election it’s all over with the COVID-19 will not be either existing or it will be described as a Sara 2 we have a cure for Covid it’s called HYDROQUOROQUIN and z pac u can get this in USA and it is safe https://twitter.com/jim_jordan/status/1291347950753525761 …	0	0	0	NaN	4852143	151483.0	60	4.683333	31	341	['in', 'is', 'all', 'a', 'and', 'after', 'the', 'all', 'over', 'with', 'the', 'will', 'not', 'be', 'or', 'it', 'will', 'be', 'as', 'a', 'we', 'have', 'a', 'for', 'and', 'can', 'this', 'in', 'and', 'it', 'is']	like opposite high school political ploy election covid either existing described sara cure covid called hydroquoroquin safe	0.165000	The Hill/HarrisXThe Hill	2020-08-02	2020-08-05	2850 RV	1.8	43.0	40.0	3.0	6	Good Response
17474	17474	1596672000000000000	pppjain	Modiji Should be honoured With Covid Memorial prize for Highest Covid Cases in India and helping 150 countries in fighting Corona. He did not fight in India as he is not selfish. You will have to wait soon we will cross USA. #COVID__19 https://twitter.com/aabidmagami/status/1291350141186670593 …	0	3	2	NaN	4852143	151483.0	45	5.600000	17	297	['be', 'for', 'in', 'and', 'in', 'did', 'not', 'in', 'as', 'he', 'is', 'not', 'will', 'have', 'to', 'we', 'will']	modiji honoured covid memorial prize highest covid cases india helping countries fighting corona fight india selfish wait soon cross covid__	-0.250000	The Hill/HarrisXThe Hill	2020-08-02	2020-08-05	2850 RV	1.8	43.0	40.0	3.0	6	Good Response
17475	17475	1596672000000000000	carman17838926	THANKS BE TO TRUMP AND THE WEALTHY GOP SENATORS WHO ABANDONED THESE POOR FOLKS, ESPECIALLY INCLUDING THEIR OWN MILLIONAIRE SENATORS CASSIDY AND KENNEDY😩\nThe rare case of a state ravaged twice by COVID-19 — USA TODAY	0	0	0	NaN	4852143	151483.0	36	5.000000	3	216	['of', 'a', 'by']	thanks trump wealthy senators abandoned poor folks especially including millionaire senators cassidy kennedy rare case state ravaged twice covid today	0.120000	The Hill/HarrisXThe Hill	2020-08-02	2020-08-05	2850 RV	1.8	43.0	40.0	3.0	6	Good Response
17476	17476	1596672000000000000	renterialawfirm	USA TODAY: 'We're in for a bad and rocky ride:' Ex-WHO doctor who helped eradicate smallpox predicts COVID-19 turmoil for years.\n https://www.usatoday.com/story/news/health/2020/08/03/covid-19-us-who-doctor-larry-brilliant/5574854002/ …	0	0	0	NaN	4852143	151483.0	22	9.260870	6	236	['in', 'for', 'a', 'and', 'who', 'for']	today rocky ride exwho doctor helped eradicate smallpox predicts covid turmoil years	0.000000	The Hill/HarrisXThe Hill	2020-08-02	2020-08-05	2850 RV	1.8	43.0	40.0	3.0	6	Good Response
17477	17477	1596672000000000000	squarerootal2	Places where Covid-19 thrives and people are dying - USA. Places where it has been flattened and deaths are low- Europe, Scandinavia, China, Australia, NZ. Why? Our President has no national plan and his comrades like @Jim_Jordan think that’s ok.	2	0	3	NaN	4852143	151483.0	40	5.175000	13	246	['where', 'and', 'are', 'where', 'it', 'has', 'been', 'and', 'are', 'has', 'no', 'and', 'his']	places covid thrives people dying places flattened deaths europe scandinavia china australia president national plan comrades like jim_jordan think thats	0.000000	The Hill/HarrisXThe Hill	2020-08-02	2020-08-05	2850 RV	1.8	43.0	40.0	3.0	6	Good Response
17478	17478	1596672000000000000	miasrule	Agreed. And let’s be clear, taking the current Covid-19 disaster out of it, it’s not just our fellow USA humans we are good at killing. Violence is American as apple pie.	1	0	0	NaN	4852143	151483.0	31	4.516129	12	170	['be', 'the', 'out', 'of', 'not', 'just', 'our', 'we', 'are', 'at', 'is', 'as']	agreed lets clear taking current covid disaster fellow humans good killing violence american apple	0.200000	The Hill/HarrisXThe Hill	2020-08-02	2020-08-05	2850 RV	1.8	43.0	40.0	3.0	6	Good Response
17479	17479	1596672000000000000	lindalouwhoh	When it comes to Covid-19, USA resembles not wealthy & powerful countries but instead far poorer countries, like Brazil, Peru and South Africa, or those with large migrant populations, like Bahrain and Oman\n\nThe Unique U.S. Failure to Control the Virus https://nyti.ms/3kfpzvj	0	0	0	NaN	4852143	151483.0	42	5.571429	11	278	['it', 'to', 'not', 'but', 'and', 'or', 'those', 'with', 'and', 'to', 'the']	comes covid resembles wealthy powerful countries instead poorer countries like brazil peru south africa large migrant populations like bahrain oman unique failure control virus	0.214524	The Hill/HarrisXThe Hill	2020-08-02	2020-08-05	2850 RV	1.8	43.0	40.0	3.0	6	Good Response
17480	17480	1596672000000000000	acai_w	WoW, such a bold and honest statement and brought to you with a lot of integrity .... Please give us an update of the Covid-19 spread in the country and how the USA is handling it? Give us an update on to whom the Bailouts are being paid out and why? Etc. etc. https://twitter.com/thehill/status/1291018874259791872 …	0	0	0	NaN	4852143	151483.0	55	4.781818	27	318	['such', 'a', 'and', 'and', 'to', 'you', 'with', 'a', 'of', 'an', 'of', 'the', 'in', 'the', 'and', 'how', 'the', 'is', 'an', 'on', 'to', 'whom', 'the', 'are', 'being', 'out', 'and']	bold honest statement brought integrity please give update covid spread country handling give update bailouts paid	0.466667	The Hill/HarrisXThe Hill	2020-08-02	2020-08-05	2850 RV	1.8	43.0	40.0	3.0	6	Good Response

Overview

Variables

Interactions

Correlations

Pearson's r

Spearman's ρ

Kendall's τ

Phik (φk)

Cramér's V (φc)

Missing values

Sample

First rows

Last rows